9
Aggregating Gridded Data Aggregating time points: 10,000's of data files: sst[latitude][longitude] become one virtual dataset: sst[time][latitude][longitude] Aggregating variables: Many files with one variable per file become one virtual dataset with all variables

11
Aggregating In-Situ and Tabular Data A database-like table with rows and columns E.g., One file has data for one buoy for one month. It isn't a multi-dimensional grid. There are no dimensions. Aggregating features and time points: Features: stations, trajectories, profiles,... Append into a giant virtual table.

15
Summary: Huge Advantages of Aggregation and Subsetting Users can find and deal with one aggregated dataset. Users can make one subset request to one aggregated dataset Grids: indices to get a temporal and spatial subset. Tables (selection constraints): any subset you want. (Not: one subset request to each unaggregated file, or worse, using FTP to download lots of entire files.) Don't treat tabular/in-situ data like gridded data.